高等学校投资效益的评价体系探讨

分析高等学校的投入产出关系,建立了一套高等学校投资效益评价指标体系和权重体系,通过模糊数学中隶属度的概念,采用层次分析法针对评价体系进行单因素模糊评价和多级模糊综合评判,并采集了某所高校不同年度的数据,通过软件对评价体系进行了计算和验证,得出各年度投资效益的产出率。     

运用案例教学法培养优秀公关人才

新时期要求高等教育培养出来的学生既要掌握扎实的理论知识,又要有实践操作技能。公共关系案例教学是集理论教学与能力培养于一体的科学有效的教学方法,在理论学习的基础上,通过对案例的讨论、分析,激发学生对“公共关系”这门课的学习兴趣,从而提高学生发现问题、分析问题的能力,沟通、协调能力和创新、决策能力。为将来从事营销公关工作做好充分准备。     

日常语义分析方法及其意义--评黄展骥语义分析方法

黄展骥先生历来注重谬误研究,倡导“批判思维”、“独立思考”。他的学术研究方法主要是西方日常语言学派的语义分析方法。倡导和运用这种方法,有利于改善我们学术界的学术风气和批判精神。因为没有批判便没有真正的思想。     

论案例教学在思想政治教育课教学中的运用

案例教学的主要特征是:讨论对话而非灌输独白,集体合作而非个体单干,批判反思而非结论教条。思想政治教育课运用案例教学,有利于学生贴近现实生活,提高分析、解决社会思想政治实际问题的能力,学习参与社会政治事务,培养思想政治创新精神和创新能力。案例教学应遵循准备、阅读分析案例、课堂讨论、课堂评价程序,编制高质量案例,优化教师案例教学的知识结构,更新并培育师生的共同学习习惯。     

为无名氏正名

无名氏并不是传统文学评论家所认为的“性爱作家”、“反动文人”,而是一位为人类而艺术的作家,虽然他在多难的20世纪40年代仍醉心于描写浪漫奇艳的爱情故事,但是,无名氏在作品中还对人类命运和文化的“圆全”进行探究。浪漫、神秘、传奇的风格,使无名氏作品艺术的纯美与深邃的哲学探寻得到了和谐的契合,并给中国读者们带来新鲜、独特的阅读感受。浪漫主义、现实主义和现代主义的大融合,是无名氏作品写作手法的特点,也为中国当代文学的发展起到了先验性的作用。     

Estimating monotone convex functions via sequential shape modification

We propose a sequential method to estimate monotone convex functions that consists of: (i) monotone regression via solving a constrained least square (LS) problem and (ii) convexification of the monotone regression estimate via solving a uniform approximation problem with associated constraints. We show that this method is faster than the constrained LS method. The ratio of computation time increases as data size increases. Moreover, we show that, under an appropriate smoothness condition, the uniform convergence rate achieved by the proposed method is nearly comparable to the best achievable rate for a non-parametric estimate which ignores the shape constraint. Simulation studies show that our method is comparable to the constrained LS method in estimation error. We illustrate our method by analysing ground water level data of wells in Korea.     

A method for estimating parameters and quantiles of the three-parameter inverse Gaussian distribution based on statistics invariant to unknown location

The inverse Gaussian (IG) distribution, also known as the Wald distribution, is a long-tailed positively skewed distribution and a well-known lifetime distribution. In this paper, we propose an efficient method of estimation for the parameters and quantiles of the three-parameter IG distribution, which is based on statistics invariant to unknown location. Through a Monte Carlo simulation study, we then show that the proposed method performs well compared with other prominent methods in terms of bias and variance. Finally, we present two illustrative examples.     

Higher order inference for stress–strength reliability with independent Burr-type X distributions

In this paper, a small-sample asymptotic method is proposed for higher order inference in the stress–strength reliability model, R=P(Y<X), where X and Y are distributed independently as Burr-type X distributions. In a departure from the current literature, we allow the scale parameters of the two distributions to differ, and the likelihood-based third-order inference procedure is applied to obtain inference for R. The difficulty of the implementation of the method is in obtaining the the constrained maximum likelihood estimates (MLE). A penalized likelihood method is proposed to handle the numerical complications of maximizing the constrained likelihood model. The proposed procedures are illustrated using a sample of carbon fibre strength data. Our results from simulation studies comparing the coverage probabilities of the proposed small-sample asymptotic method with some existing large-sample asymptotic methods show that the proposed method is very accurate even when the sample sizes are small.     

Confidence interval estimation for negative binomial group distribution

Negative binomial group distribution was proposed in the literature which was motivated by inverse sampling when considering group inspection: products are inspected group by group, and the number of non-conforming items of a group is recorded only until the inspection of the whole group is finished. The non-conforming probability p of the population is thus the parameter of interest. In this paper, the confidence interval construction for this parameter is investigated. The common normal approximation and exact method are applied. To overcome the drawbacks of these commonly used methods, a composite method that is based on the confidence intervals of the negative binomial distribution is proposed, which benefits from the relationship between negative binomial distribution and negative binomial group distribution. Simulation studies are carried out to examine the performances of our methods. A real data example is also presented to illustrate the application of our method.     

Analysis of non-repairable cold-standby systems in Bayes theory

ABSTRACT

In this paper, we seek to analyse the reliability of k-out-of-n cold-standby system with components having Weibull time-to-failure distribution in view of Bayes theory. At first, we review the existing methods exhaustively and find that all these methods have not considered Bayes theory. Then we modify the simplest method and propose new methods based on Monte Carlo simulation. Next, we combine all the information to derive the posterior distribution of Weibull parameters. A robust and universal sample-based method is proposed according to the Monte Carlo Markov Chain method to draw the sample of parameters to obtain the Bayes estimate of reliability. The drawn samples are proved to be rather satisfactory. Conducting a simulation study to compare all the methods in terms of accuracy and computational time, we have presented some useful recommendations from the simulation results. These conclusions would provide insight on the application for k-out-of-n cold-standby system.